Habitual foot strike pattern does not affect simulated triceps surae muscle metabolic energy consumption during running

Forces experienced at different levels of the musculoskeletal system during horizontal decelerations

Horizontal decelerations are frequently performed during team sports and are closely linked to sports performance and injury. This study aims to provide a comprehensive description of the kinetic demands of decelerations at the whole-body, structural, and tissue-specific levels of the musculoskeletal system. Team-sports athletes performed maximal-effort horizontal decelerations whilst full-body kinematics and ground reaction forces (GRFs) were recorded. A musculoskeletal model was used to determine whole-body (GRFs), structural (ankle, knee, and hip joint moments and contact forces), and tissue (twelve lower-limb muscle forces) loads. External GRFs in this study, especially in the horizontal direction, were up to six times those experienced during accelerated or constant-speed running reported in the literature. To cope with these high external forces, large joint moments (hip immediately after touchdown; ankle and knee during mid and late stance) and contact forces (ankle, knee, hip immediately after touchdown) were observed. Furthermore, eccentric force requirements of the tibialis anterior, soleus, quadriceps, and gluteal muscles were particularly high. The presented loading patterns provide the first empirical explanations for why decelerating movements are amongst the most challenging in team sports and can help inform deceleration-specific training prescription to target horizontal deceleration performance, or fatigue and injury resistance in team-sports athletes.

Inter-Individual Variability in Muscle Fiber-Type Distribution Affects Running Economy but Not Running Gait at Submaximal Running Speeds

Running economy is an important determinant of endurance running performance, yet insights into characteristics contributing to its inter-individual variability remain limited. Although slow-twitch muscle fibers are more energy-efficient than fast-twitch fibers during the (near-)isometric contractions common during submaximal running, current literature lacks a consensus on whether a relationship between muscle fiber-type distribution and running economy exists. This study aims to resolve the ongoing debate by addressing potential confounding factors often overlooked in prior research, such as the effect of different running speeds, the homogeneity of investigated groups, and the potential impact of the adopted running gait. We selected two groups with predetermined distinct muscle fiber-type distribution in their triceps surae muscle by measurement of carnosine via 1H-MRS, one predominantly slow (ST; n = 11; carnosine z-score = -1.31) and the other predominantly fast (FT; n = 10; z-score = 0.83). Across a range of running speeds (2-4 m/s), we measured running economy (W/kg) through indirect calorimetry, along with running kinematics, kinetics and muscle activity of the lower limb. The ST-group exhibited, on average, 7.8% better running economy than the FT-group (p = 0.01) and this difference was consistent across speeds. Both groups demonstrated almost identical kinematics, kinetics, and muscle activity patterns across submaximal running speeds. Overall, our findings indicate that distinct muscle fiber-type distribution explains some of the observed variability in running economy, for which a predominance of energy-efficient slow-twitch fibers appear beneficial. In contrast, muscle fiber-type distribution does not affect running gait substantially.

Plantar Flexor Muscle Activity and Fascicle Behavior in Gastrocnemius Medialis During Running in Highly Cushioned Shoes With Carbon-Fiber Plates

The purposes of this study were to clarify the electromyography (EMG) of plantar flexors and to analyze the fascicle and tendon behaviors of the gastrocnemius medialis (GM) during running in the carbon-fiber plate embedded in thicker midsole racing shoes, such as the Nike ZoomX Vaporfly (VF) and traditional racing shoes (TRAD). We compared the fascicle and series elastic element behavior of the GM and EMG of the lower limb muscles during running (14 km/h, 45 s) in athletes wearing VF or TRAD. GM EMGs in the push-off phase were approximately 50% lower in athletes wearing VF than in TRAD. Although the series elastic element behavior and/or mean fascicle-shortening velocity during the entire stance phase were not significantly different between VF and TRAD, a significant difference was found in both the mean EMG and integral EMG of the GM during the push-off phase. EMG of the gastrocnemius lateralis (GL) during the first half of the push-off phase was significantly different between VF and TRAD. Present results suggest that VF facilitates running propulsion, resulting in a decrease in GM and GL EMGs at a given running velocity during the push-off phase, leading to a reduction in metabolic cost.

Muscle fibre typology affects whole-body metabolic rate during isolated muscle contractions and human locomotion

The wide variation in muscle fibre type distribution across individuals, along with the very different energy consumption rates in slow versus fast muscle fibres, suggests that muscle fibre typology contributes to inter-individual differences in metabolic rate during exercise. However, this has been hard to demonstrate due to the gap between a single muscle fibre and full-body exercises. We investigated the isolated effect of triceps surae muscle contraction velocity on whole-body metabolic rate during cyclic contractions in individuals a priori selected for their predominantly slow (n = 11) or fast (n = 10) muscle fibre typology by means of proton magnetic resonance spectroscopy (1H-MRS). Subsequently, we examined their whole-body metabolic rate during walking and running at 2 m/s, exercises with comparable metabolic rates but distinct triceps surae muscle force and velocity demands (walking: low force, high velocity; running: high force, low velocity). Increasing triceps surae contraction velocity during cyclic contractions elevated net whole-body metabolic rate for both typology groups. However, the slow group consumed substantially less net metabolic energy at the slowest contraction velocity, but the metabolic difference between groups diminished at faster velocities. Consistent with the more economic force production during slow contractions, the slow group exhibited lower metabolic rates than the fast group while running, whereas metabolic rates were similar during walking. These findings provide important insights into the influence of muscle fibre typology on whole-body metabolic rate and emphasize the importance of considering muscle mechanical demands to understand muscle fibre typology related differences in whole-body metabolic rates. KEY POINTS: Muscle fibre typology is often suggested to affect whole-body metabolic rate, yet convincing in vivo evidence is lacking. Using isolated plantar flexor muscle contractions in individuals a priori selected for their predominantly slow or fast muscle fibre typology, we demonstrated that having predominantly slow muscle fibres provides a metabolic advantage during slow muscle contractions, but this benefit disappeared at faster contractions. We extended these results to full-body exercises, where we demonstrated that higher proportions of slow fibres associated with better economy during running but not when walking. These findings provide important insights into the influence of muscle fibre typology on whole-body metabolic rate and emphasize the importance of considering muscle mechanical demands to understand muscle fibre typology related differences in whole-body metabolic rate.

Effects of gait retraining using minimalist shoes on the medial gastrocnemius muscle-tendon unit behavior and dynamics during running

The effects of a 12-week gait retraining program on the adaptation of the medial gastrocnemius (MG) and muscle-tendon unit (MTU) were investigated. 26 runners with a rearfoot strike pattern (RFS) were randomly assigned to one of two groups: gait retraining (GR) or control group (CON). MG ultrasound images, marker positions, and ground reaction forces (GRF) were collected twice during 9 km/h of treadmill running before and after the intervention. Ankle kinetics and the MG and MTU behavior and dynamics were quantified. Runners in the GR performed gradual 12-week gait retraining transitioning to a forefoot strike pattern. After 12-week, (1) ten participants in each group completed the training; eight participants in GR transitioned to non-RFS with reduced foot strike angles; (2) MG fascicle contraction length and velocity significantly decreased after the intervention for both groups, whereas MG forces increased after intervention for both groups; (3) significant increases in MTU stretching length for GR and peak MTU recoiling velocity for both groups were observed after the intervention, respectively; (4) no significant difference was found for all parameters of the series elastic element. Gait retraining might potentially influence the MG to operate at lower fascicle contraction lengths and velocities and produce greater peak forces. The gait retraining had no effect on SEE behavior and dynamics but did impact MTU, suggesting that the training was insufficient to induce mechanical loading changes on SEE behavior and dynamics.

OpenCap: Human movement dynamics from smartphone videos

Measures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies or clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing both the kinematics (i.e., motion) and dynamics (i.e., forces) of human movement using videos captured from two or more smartphones. OpenCap leverages pose estimation algorithms to identify body landmarks from videos; deep learning and biomechanical models to estimate three-dimensional kinematics; and physics-based simulations to estimate muscle activations and musculoskeletal dynamics. OpenCap's web application enables users to collect synchronous videos and visualize movement data that is automatically processed in the cloud, thereby eliminating the need for specialized hardware, software, and expertise. We show that OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions. Additionally, we demonstrate OpenCap's practical utility through a 100-subject field study, where a clinician using OpenCap estimated musculoskeletal dynamics 25 times faster than a laboratory-based approach at less than 1% of the cost. By democratizing access to human movement analysis, OpenCap can accelerate the incorporation of biomechanical metrics into large-scale research studies, clinical trials, and clinical practice.

Evaluation of musculoskeletal models, scaling methods, and performance criteria for estimating muscle excitations and fiber lengths across walking speeds

Muscle-driven simulations have been widely adopted to study muscle-tendon behavior; several generic musculoskeletal models have been developed, and their biofidelity improved based on available experimental data and computational feasibility. It is, however, not clear which, if any, of these models accurately estimate muscle-tendon dynamics over a range of walking speeds. In addition, the interaction between model selection, performance criteria to solve muscle redundancy, and approaches for scaling muscle-tendon properties remain unclear. This study aims to compare estimated muscle excitations and muscle fiber lengths, qualitatively and quantitatively, from several model combinations to experimental observations. We tested three generic models proposed by Hamner et al., Rajagopal et al., and Lai-Arnold et al. in combination with performance criteria based on minimization of muscle effort to the power of 2, 3, 5, and 10, and four approaches to scale the muscle-tendon unit properties of maximum isometric force, optimal fiber length, and tendon slack length. We collected motion analysis and electromyography data in eight able-bodied subjects walking at seven speeds and compared agreement between estimated/modelled muscle excitations and observed muscle excitations from electromyography and computed normalized fiber lengths to values reported in the literature. We found that best agreement in on/off timing in vastus lateralis, vastus medialis, tibialis anterior, gastrocnemius lateralis, gastrocnemius medialis, and soleus was estimated with minimum squared muscle effort than to higher exponents, regardless of model and scaling approach. Also, minimum squared or cubed muscle effort with only a subset of muscle-tendon unit scaling approaches produced the best time-series agreement and best estimates of the increment of muscle excitation magnitude across walking speeds. There were discrepancies in estimated fiber lengths and muscle excitations among the models, with the largest discrepancy in the Hamner et al. model. The model proposed by Lai-Arnold et al. best estimated muscle excitation estimates overall, but failed to estimate realistic muscle fiber lengths, which were better estimated with the model proposed by Rajagopal et al. No single model combination estimated the most accurate muscle excitations for all muscles; commonly observed disagreements include onset delay, underestimated co-activation, and failure to estimate muscle excitation increments across walking speeds.

Triceps surae muscle force potential and force demand shift with altering stride frequency in running

While it is well recognized that the preferred stride frequency (PSF) in running closely corresponds to the metabolically optimal frequency, the underlying mechanisms are still unclear. Changes in joint kinematics when altering stride frequency will affect the muscle-tendon unit lengths and potentially the efficiency of muscles crossing these joints. Here, we investigated how fascicle kinematics and forces of the triceps surae muscle, a highly energy consuming muscle, are affected when running at different stride frequencies. Twelve runners ran on a force measuring treadmill, adopting five different frequencies (PSF; PSF±8%; PSF±15%), while we measured joint kinematics, whole-body energy expenditure, triceps surae muscle activity, and soleus (SOL; N = 10) and gastrocnemius medialis (GM; N = 12) fascicle kinematics. In addition, we used dynamic optimization to estimate SOL and GM muscle forces. We found that SOL and GM mean muscle fascicle length during stance followed an inverted U-relationship with the longest fascicle lengths occurring at PSF. Fascicle lengths were shortest at frequencies lower than PSF. In addition, average SOL force was greater at PSF-15% compared to PSF. Overall, our results suggest that reduced SOL and GM muscle fascicle lengths, associated with reduced muscle force potential, together with greater SOL force demand, contribute to the increased whole-body energy expenditure when running at lower than PSF. At higher stride frequencies, triceps surae muscle kinematics and force production were less affected suggesting that increased energy expenditure is rather related to higher cost of leg swing and greater cost of force production.

Modeling toes contributes to realistic stance knee mechanics in three-dimensional predictive simulations of walking

Physics-based predictive simulations have been shown to capture many salient features of human walking. Yet they often fail to produce realistic stance knee and ankle mechanics. While the influence of the performance criterion on the predicted walking pattern has been previously studied, the influence of musculoskeletal mechanics has been less explored. Here, we investigated the influence of two mechanical assumptions on the predicted walking pattern: the complexity of the foot model and the stiffness of the Achilles tendon. We found, through three-dimensional muscle-driven predictive simulations of walking, that modeling the toes, and thus using two-segment instead of single-segment foot models, contributed to robustly eliciting physiological stance knee flexion angles, knee extension torques, and knee extensor activity. Modeling toes also slightly decreased the first vertical ground reaction force peak, increasing its agreement with experimental data, and improved stance ankle kinetics. It nevertheless slightly worsened predictions of ankle kinematics. Decreasing Achilles tendon stiffness improved the realism of ankle kinematics, but there remain large discrepancies with experimental data. Overall, this simulation study shows that not only the performance criterion but also mechanical assumptions affect predictive simulations of walking. Improving the realism of predictive simulations is required for their application in clinical contexts. Here, we suggest that using more complex foot models might contribute to such realism.